Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

15:19:57 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.3 / v1.14.3-4-ga7b402c)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.now(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

15:19:57 WARNING opendrift.models.shipdrift:181: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
15:19:57 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
15:20:01 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
15:20:01 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
15:20:01 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
15:20:01 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
15:20:01 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

15:20:01 INFO    opendrift:1789: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
15:20:01 INFO    opendrift:1789: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
15:20:01 INFO    opendrift:944: Using existing reader for land_binary_mask to move elements to ocean
15:20:01 INFO    opendrift:974: All points are in ocean
15:20:01 INFO    opendrift:2085: 2025-09-12 15:19:57.297080 - step 1 of 24 - 1000 active elements (0 deactivated)
15:20:01 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:04 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
15:20:04 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:05 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
15:20:05 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:07 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
15:20:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:11 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:11 INFO    opendrift:2085: 2025-09-12 16:19:57.297080 - step 2 of 24 - 1000 active elements (0 deactivated)
15:20:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:12 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:12 INFO    opendrift:2085: 2025-09-12 17:19:57.297080 - step 3 of 24 - 1000 active elements (0 deactivated)
15:20:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:14 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:14 INFO    opendrift:2085: 2025-09-12 18:19:57.297080 - step 4 of 24 - 1000 active elements (0 deactivated)
15:20:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:16 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:16 INFO    opendrift:2085: 2025-09-12 19:19:57.297080 - step 5 of 24 - 1000 active elements (0 deactivated)
15:20:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:17 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:17 INFO    opendrift:2085: 2025-09-12 20:19:57.297080 - step 6 of 24 - 1000 active elements (0 deactivated)
15:20:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:19 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:19 INFO    opendrift:2085: 2025-09-12 21:19:57.297080 - step 7 of 24 - 1000 active elements (0 deactivated)
15:20:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:21 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:21 INFO    opendrift:2085: 2025-09-12 22:19:57.297080 - step 8 of 24 - 1000 active elements (0 deactivated)
15:20:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:23 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:23 INFO    opendrift:2085: 2025-09-12 23:19:57.297080 - step 9 of 24 - 1000 active elements (0 deactivated)
15:20:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:24 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:24 INFO    opendrift:2085: 2025-09-13 00:19:57.297080 - step 10 of 24 - 1000 active elements (0 deactivated)
15:20:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:26 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:26 INFO    opendrift:2085: 2025-09-13 01:19:57.297080 - step 11 of 24 - 1000 active elements (0 deactivated)
15:20:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:28 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:28 INFO    opendrift:2085: 2025-09-13 02:19:57.297080 - step 12 of 24 - 1000 active elements (0 deactivated)
15:20:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:30 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:30 INFO    opendrift:2085: 2025-09-13 03:19:57.297080 - step 13 of 24 - 1000 active elements (0 deactivated)
15:20:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:32 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:32 INFO    opendrift:2085: 2025-09-13 04:19:57.297080 - step 14 of 24 - 1000 active elements (0 deactivated)
15:20:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:34 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:34 INFO    opendrift:2085: 2025-09-13 05:19:57.297080 - step 15 of 24 - 1000 active elements (0 deactivated)
15:20:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:36 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:36 INFO    opendrift:2085: 2025-09-13 06:19:57.297080 - step 16 of 24 - 1000 active elements (0 deactivated)
15:20:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:38 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:38 INFO    opendrift:2085: 2025-09-13 07:19:57.297080 - step 17 of 24 - 1000 active elements (0 deactivated)
15:20:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:40 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:40 INFO    opendrift:2085: 2025-09-13 08:19:57.297080 - step 18 of 24 - 1000 active elements (0 deactivated)
15:20:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:42 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:42 INFO    opendrift:2085: 2025-09-13 09:19:57.297080 - step 19 of 24 - 1000 active elements (0 deactivated)
15:20:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:44 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:44 INFO    opendrift:2085: 2025-09-13 10:19:57.297080 - step 20 of 24 - 1000 active elements (0 deactivated)
15:20:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:46 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:46 INFO    opendrift:2085: 2025-09-13 11:19:57.297080 - step 21 of 24 - 1000 active elements (0 deactivated)
15:20:47 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:47 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:48 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:48 INFO    opendrift:2085: 2025-09-13 12:19:57.297080 - step 22 of 24 - 1000 active elements (0 deactivated)
15:20:49 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:49 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:50 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:50 INFO    opendrift:2085: 2025-09-13 13:19:57.297080 - step 23 of 24 - 1000 active elements (0 deactivated)
15:20:51 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:51 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:52 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:52 INFO    opendrift:2085: 2025-09-13 14:19:57.297080 - step 24 of 24 - 1000 active elements (0 deactivated)
15:20:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:54 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 2MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/24)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    x_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/96)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))

  • time
    (time)
    datetime64[ns]
    2025-09-12T15:19:57.297080 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-09-12T15:19:57.297080000', '2025-09-12T16:19:57.297080000',
           '2025-09-12T17:19:57.297080000', '2025-09-12T18:19:57.297080000',
           '2025-09-12T19:19:57.297080000', '2025-09-12T20:19:57.297080000',
           '2025-09-12T21:19:57.297080000', '2025-09-12T22:19:57.297080000',
           '2025-09-12T23:19:57.297080000', '2025-09-13T00:19:57.297080000',
           '2025-09-13T01:19:57.297080000', '2025-09-13T02:19:57.297080000',
           '2025-09-13T03:19:57.297080000', '2025-09-13T04:19:57.297080000',
           '2025-09-13T05:19:57.297080000', '2025-09-13T06:19:57.297080000',
           '2025-09-13T07:19:57.297080000', '2025-09-13T08:19:57.297080000',
           '2025-09-13T09:19:57.297080000', '2025-09-13T10:19:57.297080000',
           '2025-09-13T11:19:57.297080000', '2025-09-13T12:19:57.297080000',
           '2025-09-13T13:19:57.297080000', '2025-09-13T14:19:57.297080000',
           '2025-09-13T15:19:57.297080000'], dtype='datetime64[ns]')

• Data variables: (24)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          shape=(1000, 25), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 5.024 5.048 ... 5.678 5.701

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.8801017

    maxval :

    5.9832287

    array([[5.0348186, 5.023987 , 5.048273 , ..., 5.4550076, 5.4756284,
            5.478512 ],
           [5.007899 , 4.995967 , 5.045531 , ..., 5.7375546, 5.7391963,
            5.697305 ],
           [5.0193124, 5.0328426, 5.0509467, ..., 5.646643 , 5.6573315,
            5.6641083],
           ...,
           [5.0018587, 5.020696 , 5.060232 , ..., 5.815951 , 5.8428245,
            5.850316 ],
           [4.9773602, 4.967834 , 4.983716 , ..., 5.351402 , 5.389403 ,
            5.433007 ],
           [4.9929357, 5.007909 , 5.0364904, ..., 5.6821356, 5.678214 ,
            5.7008367]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.04 63.07 ... 63.38 63.38

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.973133

    maxval :

    63.616932

    array([[63.004982, 63.041508, 63.070187, ..., 63.472706, 63.490788,
            63.489098],
           [63.008007, 63.035095, 63.05508 , ..., 63.354465, 63.364716,
            63.362225],
           [62.99621 , 63.02074 , 63.03656 , ..., 63.44039 , 63.454758,
            63.464783],
           ...,
           [63.001423, 63.02498 , 63.04725 , ..., 63.42535 , 63.415394,
            63.425182],
           [62.989754, 63.02821 , 63.05928 , ..., 63.508293, 63.50934 ,
            63.52158 ],
           [62.98824 , 63.005264, 63.031925, ..., 63.366447, 63.37817 ,
            63.378563]], shape=(1000, 25), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]],
          shape=(1000, 25), dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], shape=(1000, 25), dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], shape=(1000, 25), dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]],
          shape=(1000, 25), dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]],
          shape=(1000, 25), dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]],
          shape=(1000, 25), dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]],
          shape=(1000, 25), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    2.818 2.208 1.964 ... 0.2976 0.2976

    minval :

    -5.0483727

    maxval :

    7.2743897

    array([[ 2.8182783 ,  2.2080495 ,  1.9644938 , ...,  0.513702  ,
            -0.19984369, -0.19984369],
           [ 0.7358947 ,  1.2703553 , -0.0090911 , ..., -1.7899846 ,
            -3.0595841 , -3.0595841 ],
           [ 1.3202435 ,  0.6808522 , -0.23424475, ...,  1.4824667 ,
             1.6640778 ,  1.6640778 ],
           ...,
           [ 4.015289  ,  3.5880046 ,  1.3640946 , ...,  0.25809026,
            -0.66336447, -0.66336447],
           [ 0.44104534,  1.4774189 ,  1.084317  , ..., -0.3852518 ,
             0.08031555,  0.08031555],
           [-2.1785097 , -1.1062169 , -0.8666317 , ...,  0.18689719,
             0.29755485,  0.29755485]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    7.288 10.1 11.46 ... 3.725 3.725

    minval :

    -0.19556956

    maxval :

    14.4555645

    array([[ 7.2882843, 10.099178 , 11.4611435, ...,  4.933212 ,  3.8084943,
             3.8084943],
           [ 5.5293627,  9.278338 ,  9.697187 , ...,  3.292126 ,  1.9324162,
             1.9324162],
           [ 7.8490343, 10.568969 , 10.568031 , ...,  5.85805  ,  5.1634326,
             5.1634326],
           ...,
           [ 6.5459175, 10.070046 , 11.045376 , ...,  4.8509192,  4.3234663,
             4.3234663],
           [ 8.212464 , 11.299074 , 12.530282 , ...,  5.609336 ,  4.348474 ,
             4.348474 ],
           [ 3.6512554,  5.3467884,  8.198387 , ...,  5.155685 ,  3.7248774,
             3.7248774]], shape=(1000, 25), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.154 0.1536 ... 0.09514 0.09514

    minval :

    -0.015735645

    maxval :

    0.4968702

    array([[0.15396197, 0.15363681, 0.20621446, ..., 0.2595849 , 0.16842125,
            0.16842125],
           [0.14297599, 0.15097377, 0.20586747, ..., 0.13102448, 0.11157712,
            0.11157712],
           [0.16229928, 0.18400966, 0.22856946, ..., 0.14990649, 0.10477874,
            0.10477874],
           ...,
           [0.15025221, 0.17379172, 0.21986914, ..., 0.08716078, 0.08696952,
            0.08696952],
           [0.16140302, 0.15178698, 0.17305407, ..., 0.26300594, 0.19250475,
            0.19250475],
           [0.16737108, 0.200555  , 0.23032986, ..., 0.12985727, 0.09513913,
            0.09513913]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.4625 0.4345 ... 0.1685 0.1685

    minval :

    0.032362096

    maxval :

    0.51380026

    array([[0.4625257 , 0.4344649 , 0.40857533, ..., 0.11013577, 0.11097018,
            0.11097018],
           [0.4647782 , 0.44318864, 0.42637715, ..., 0.1555786 , 0.18401624,
            0.18401624],
           [0.4788921 , 0.45916033, 0.44442096, ..., 0.1362066 , 0.1710724 ,
            0.1710724 ],
           ...,
           [0.47607   , 0.4552888 , 0.43153712, ..., 0.16938804, 0.19938572,
            0.19938572],
           [0.49522573, 0.44678095, 0.4071884 , ..., 0.0788782 , 0.05421994,
            0.05421994],
           [0.49523094, 0.48578846, 0.45238236, ..., 0.13971847, 0.16847186,
            0.16847186]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.02582 0.03746 ... 0.03809 0.03809

    minval :

    0.01880895

    maxval :

    0.12306703

    array([[0.02581992, 0.03746313, 0.05351477, ..., 0.0564987 , 0.05037631,
            0.05037631],
           [0.02480964, 0.03606625, 0.05516788, ..., 0.04316068, 0.03485841,
            0.03485841],
           [0.02742046, 0.04213338, 0.05553592, ..., 0.05275078, 0.04529745,
            0.04529745],
           ...,
           [0.02596603, 0.04028935, 0.05622504, ..., 0.04703496, 0.03132254,
            0.03132254],
           [0.02713001, 0.03606363, 0.04844742, ..., 0.0550666 , 0.05022768,
            0.05022768],
           [0.02817028, 0.04498351, 0.05434626, ..., 0.04787081, 0.03808649,
            0.03808649]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    0.114 0.1514 ... 0.05436 0.05436

    minval :

    0.040855158

    maxval :

    0.27421793

    array([[0.11395054, 0.15139109, 0.18077388, ..., 0.06297757, 0.05961806,
            0.05961806],
           [0.12226036, 0.16369861, 0.18391319, ..., 0.05434859, 0.05228388,
            0.05228388],
           [0.12143328, 0.15593773, 0.19382529, ..., 0.05462792, 0.05309298,
            0.05309298],
           ...,
           [0.12615635, 0.15866998, 0.18847392, ..., 0.05231763, 0.050251  ,
            0.050251  ],
           [0.13839032, 0.1764945 , 0.19783258, ..., 0.0697283 , 0.06112558,
            0.06112558],
           [0.13341914, 0.17103553, 0.19613975, ..., 0.05614317, 0.05436084,
            0.05436084]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    2.106 2.312 2.517 ... 2.175 2.175

    minval :

    2.0277965

    maxval :

    3.4024065

    array([[2.106167 , 2.3117988, 2.5165389, ..., 2.2291849, 2.188938 ,
            2.188938 ],
           [2.1286533, 2.3642344, 2.5227995, ..., 2.1817033, 2.14096  ,
            2.14096  ],
           [2.1255312, 2.3196998, 2.5808618, ..., 2.2393684, 2.188334 ,
            2.188334 ],
           ...,
           [2.1385264, 2.334582 , 2.5472531, ..., 2.1948225, 2.129215 ,
            2.129215 ],
           [2.1731215, 2.414277 , 2.625733 , ..., 2.2441242, 2.1955204,
            2.1955204],
           [2.157948 , 2.3679256, 2.5976582, ..., 2.2251801, 2.1749477,
            2.1749477]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    5.405 5.33 5.338 ... 6.394 6.394

    minval :

    5.1896014

    maxval :

    6.589327

    array([[5.4046407, 5.330015 , 5.3378944, ..., 6.30989  , 6.341308 ,
            6.341308 ],
           [5.355969 , 5.2886763, 5.317639 , ..., 6.419645 , 6.3561745,
            6.3561745],
           [5.3528967, 5.2910023, 5.307354 , ..., 6.5090265, 6.462974 ,
            6.462974 ],
           ...,
           [5.3289638, 5.28883  , 5.3093133, ..., 6.476505 , 6.322088 ,
            6.322088 ],
           [5.2628407, 5.2430415, 5.335902 , ..., 6.2216215, 6.3198323,
            6.3198323],
           [5.2863793, 5.2207837, 5.3100877, ..., 6.4661927, 6.39434  ,
            6.39434  ]], shape=(1000, 25), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-09-12 15:19:57.297080', '2025-09-12 16:19:57.297080',
                   '2025-09-12 17:19:57.297080', '2025-09-12 18:19:57.297080',
                   '2025-09-12 19:19:57.297080', '2025-09-12 20:19:57.297080',
                   '2025-09-12 21:19:57.297080', '2025-09-12 22:19:57.297080',
                   '2025-09-12 23:19:57.297080', '2025-09-13 00:19:57.297080',
                   '2025-09-13 01:19:57.297080', '2025-09-13 02:19:57.297080',
                   '2025-09-13 03:19:57.297080', '2025-09-13 04:19:57.297080',
                   '2025-09-13 05:19:57.297080', '2025-09-13 06:19:57.297080',
                   '2025-09-13 07:19:57.297080', '2025-09-13 08:19:57.297080',
                   '2025-09-13 09:19:57.297080', '2025-09-13 10:19:57.297080',
                   '2025-09-13 11:19:57.297080', '2025-09-13 12:19:57.297080',
                   '2025-09-13 13:19:57.297080', '2025-09-13 14:19:57.297080',
                   '2025-09-13 15:19:57.297080'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (96)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2025-09-12 15:20:01.170040

  date_created :

  2025-09-12T15:20:01.170050

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2025-09-12 15:19:57.297080

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:horizontal_diffusivity :

  100.0

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.14.3

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2025-09-12 15:20:01.234059

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2025-09-13 15:19:57.297080

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:15.4 total 0:00:00.0 preparing 0:00:15.3 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:15.4 total 0:00:00.0 preparing 0:00:15.3 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:14.4 total 0:00:00.0 preparing 0:00:14.4 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 57.1 total time 3.8 configuration 0.0 preparing main loop 0.0 moving elements to ocean 53.2 main loop 0.4 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.973133

  geospatial_lat_max :

  63.616932

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.8801017

  geospatial_lon_max :

  5.9832287

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:00:57.179621

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:15.4  total
 0:00:00.0  preparing
 0:00:15.3  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:15.4  total
 0:00:00.0  preparing
 0:00:15.3  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:14.4  total
 0:00:00.0  preparing
 0:00:14.4  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
   57.1 total time
    3.8 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
   53.2 main loop
      0.4 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.14.3)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml

Discarded readers:

Time:
        Start: 2025-09-12 15:19:57.297080 UTC
        Present: 2025-09-13 15:19:57.297080 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

15:21:16 INFO    opendrift:4612: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
15:21:32 INFO    opendrift:3053: Time to make animation: 0:00:16.968656